Factors Affecting Changes in Managerial Decisions
Bibliographic record
Abstract
ABSTRACT It is commonly held that revealed managerial decisions depend on the interaction of risk attitudes and preferences, as well as market and firm conditions. In agriculture, production plans can have a horizon of a few months to several years. However, it is not always the case that managers follow through on their plans once established. The purpose of this paper is to investigate factors that contribute to changes between managers’ planned decisions and eventual actions. A unique dataset consisting of farm financial data, consultant generated production plans, and a follow‐up producer survey was constructed with participants in the Texas FARM‐Assistance program. We evaluate the effects of managers’ behavioral attributes, farm financial indicators, and production characteristics on the decision to follow through on business plans. Our findings provide new insights into the decision‐making and planning processes of managers under risky market conditions, and the interactions of same with behavioral characteristics. [EconLit citations: Q12; Q13; Q14; D22; G02].
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".